Mutation Assessor - Colon Adenocarcinoma (Primary solid tumor)

Mutation Assessor

Colon Adenocarcinoma (Primary solid tumor)

16 April 2014 | analyses__2014_04_16

Maintainer Information

Citation Information

Maintained by David Heiman (Broad Institute)

Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Assessor. Broad Institute of MIT and Harvard. doi:10.7908/C10863W0

Overview

Introduction

This report serves to summarize the functional impact of missense mutations in each gene as determined by Mutation Assessor[1].

Summary

High Functional Impact Missense Mutations: 2413
Medium Functional Impact Missense Mutations: 13915
Low Functional Impact Missense Mutations: 13473
Neutral Functional Impact Mutations: 9535

Results

Functional Impact by Gene

Table 1. Get Full Table A gene-level breakdown of missense mutation functional impact, ordered by MutSig rank. Includes missense mutation counts broken down by level of functional impact (high, medium, low, neutral), median functional impact score and level, and most common level(s) of functional impact (mode) per gene.

Gene	MutSig Rank	High Functional Impact Count	Medium Functional Impact Count	Low Functional Impact Count	Neutral Functional Impact Count	Median Functional Impact Score	Median Functional Impact Level	Mode Functional Impact Level
APC	1	0	5	10	8	1.355	low	low
PIK3CA	2	0	14	12	7	1.620	low	medium
BRAF	3	0	0	21	0	1.320	low	low
KRAS	4	7	49	1	0	3.245	medium	medium
TP53	5	0	48	2	0	3.145	medium	medium
FBXW7	6	2	12	8	4	2.165	medium	medium
NRAS	7	6	8	1	0	3.325	medium	medium
SMAD4	8	2	13	2	0	2.790	medium	medium
FAM123B	9	0	3	0	2	2.075	medium	medium
SOX9	10	0	1	0	0	3.020	medium	medium

Methods & Data

Input

COAD-TP.maf.annotated
COAD-TP.sig_genes.txt
Mutation Assessor Scores Release 2:

hg18
hg19

A lookup is done against the relevant Mutation Assessor Scores table for each missense mutation in a given MAF file, and available functional impact score and level are appended as two new columns to generate COAD-TP.maf.annotated. These are summarized in Table 1, sorted by MutSig rank.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References

[1] Boris Reva, Yevgeniy Antipin, and Chris Sander, Predicting the functional impact of protein mutations: application to cancer genomics, Nucl. Acids Res. 39(17):e118 (2011)

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